1. Field of the Invention
The present invention relates to image and data processing systems and techniques. More specifically, the present invention relates to systems and techniques for adaptive non-uniformity compensation for focal plane arrays of infrared detectors and the like.
2. Description of the Related Art
Focal plane arrays are used in military, astronomical and other applications. For example, in military applications, focal plane arrays are often used for target acquisition and tracking. The seekers of missiles often use arrays of image detectors sensitive to energy in the visible or (more typically) infrared portion of the electromagnetic spectrum. Unfortunately, these arrays, referred to as focal plane arrays are subject to anomalies such as detector to detector nonuniformity in sensitivity, gain/offset and fixed pattern noise. While numerous techniques are known in the art for addressing detector to detector nonuniformity in sensitivity, gain/offset, and fixed pattern noise continues to be problematic.
Fixed pattern noise (FPNs) are sensor fixed artifacts induced by non-uniform response of the focal plane array (FPA). The non-uniform response causes the FPA output to be spatially varying even when illuminated by a uniform source. Techniques such as stored non-uniformity correction can correct for the non-uniform array response under static conditions. But dynamic inputs, such as changing photon flux induced by dome heating, requires dynamic or adaptive non-uniformity compensation.
Accordingly, nonuniformity compensation (NUC) systems have been developed to address detector to detector nonuniformities. In particular, adaptive nonuniformity compensation systems (ADNUC) have been developed to address fixed pattern noise in focal plane arrays of image detectors. Traditional ADNUC systems use an additive feedback algorithm wherein a correction-offset term is accumulated from an error-term which is generated from the filtered output image. The correction term is then subtracted from the next input image. Therefore, depending on the feedback coefficients (the non-linear transfer functions), it takes about 10-30 image frames for the ADNUC systems to reduce the FPN from an initial high value to a low equilibrium value. While nominally effective, this system limits the response time of the system.
In addition, conventional ADNUC systems are not designed to remove temporally correlated temporal noise. Further, because FPNs are fixed on the focal plane and hence are temporally correlated, they present a more difficult false alarm problem than that presented by temporally uncorrelated temporal noise (TN). In traditional ADNUC systems, the accumulated correction-offset terms will cause fixed-pattern artifacts, which may lead to a high number of false alarms for target detection by the missile tracking system (i.e., the "tracker").
Further, traditional systems do not remove hot-dome shading effects. Hot dome shading is a heating of the missile dome due to aerodynamic friction effects. The heat on the dome creates a thermal background image which causes a filter mismatch in the tracker and thereby limits the performance of the system.
Hence, a need remains in the art for a system and technique for addressing fixed pattern noise in focal plane arrays. Specifically, there is a need for a system and technique for rapidly addressing fixed pattern noise, including temporal noise and dome shading, in focal plane arrays of infrared image detectors.
The need in the art is addressed by copending application Ser. No. 09/175,213, filed Oct. 19, 1998 by H. Chen et al., and entitled ADAPTIVE NON-UNIFORMITY COMPENSATION USING FEEDFORWARD SHUNTING, the teachings of which are incorporated herein by reference. Chen discloses and claims a new and novel adaptive nonuniformity correction system and method which addresses many of the shortcomings associated with prior designs.
However, as per conventional teachings, the referenced application by Chen et al. teaches the utilization of anti-mean filters to remove the effects of dome shading in the main or feedback signal path. An important parameter for applying an anti-mean filter is the mean filter size which is implemented in hardware. The smaller the size, the less computational load for the system. The smaller mean filter size would also filter out more curved dome shading (a correspondingly higher spatial filter component) from being processed with the target signals. In general, the filter size implemented in hardware is about 5.times.5 (or 3.times.3). However, for a large target pattern, the anti-mean filter with a small size will distort the target pattern. For example, when a large warhead burst is processed by a 3.times.3 anti-mean filter, the burst pattern will have a hole in the center (a donut-like pattern). In addition, there will be positive and negative ringing distortion on the edge of the burst. The ringing is the main cause for fixed pattern artifacts during the conventional ADNUC process. The distortion and ringing is caused by the resulting high means when the small 3.times.3 mean filter kernel convolves across the larger burst. A similar distortion and ringing will also occur for the spatial filter in the tracker when the filter size is small compared with the size of the target.
Hence, a need remains in the art for a system and/or technique for eliminating dome shading effects in an adaptive nonuniformity correction system which does not introduce ringing distortion in an output image with large target.